Dual spatially resolved transcriptomics for human host–pathogen colocalization studies in FFPE tissue sections

Technologies to study localized host–pathogen interactions are urgently needed. Here, we present a spatial transcriptomics approach to simultaneously capture host and pathogen transcriptome-wide spatial gene expression information from human formalin-fixed paraffin-embedded (FFPE) tissue sections at a near single-cell resolution. We demonstrate this methodology in lung samples from COVID-19 patients and validate our spatial detection of SARS-CoV-2 against RNAScope and in situ sequencing. Host–pathogen colocalization analysis identified putative modulators of SARS-CoV-2 infection in human lung cells. Our approach provides new insights into host response to pathogen infection through the simultaneous, unbiased detection of two transcriptomes in FFPE samples. \mentary Information The online version contains supplementary material available at 10.1186/s13059-023-03080-y.


Figure S3 .
Figure S3.RNAScope Validation Workflow.The RNAScope validation workflow consists of two independent and similar procedures, which process the RNAScope or ST image signals respectively, and compare the two procedure outputs.In each RNAScope/ST procedure, the original histological image is cropped into median sized subimages.The RNAScope/ST signals are detected by the corresponding method.Afterwards, the signal images are cropped into small blocks, which are utilized for the validation analysis.

Figure S4 .
Figure S4.Workflow of RNAScope light-field image processing.A visualization of the RNAScope signal processing procedure, where the RNAScope signal images are the same size as the corresponding light field images.The ST signal processing shares essentially the same procedure, except for the RNAScope/ST signal call.The black scale bar represents the length of 500µm and the white bars represent the length of 50µm.

Figure S5 .
Figure S5.RNAScope Signal Call.The original tissue subimage, the hue channel, and the RNAScope signal subimage after the thresholding, where the white scale bar represents the length of 50µm, and all the images are of the same size and resolution.

Figure S6 .
Figure S6.In situ sequencing validation of ST S & E gene signal.Enlargement of Figure 1c showing the in situ sequencing (ISS) signal and ST signal for genes S and E (~300µm between ISS and ST sections).Scale bars are 550µm.

Figure S7 .
Figure S7.Viral signal across RNA detection techniques.(a) Viral copies per ng of input RNA across each COVID-19 sample section detected by qPCR.(b) Viral signal across all SARS-CoV-2 genes detected by ST, E gene detected by ST E gene detected by qPCR, and S gene detected by RNAScope.

Figure S8 .
Figure S8.Highly reproducible capture of human transcriptome data.Pearson correlation of average human gene expression between consecutive sections for each sample (n=5 samples), with either (a) one section with human and SARS-CoV-2 probes added (HS) and the other with only human probes added (H), (b) both sections with human and SARS-CoV-2 probes added (HS), or both sections with only human probes added (H), p-value < 0.05.

Figure S9 .
Figure S9.Correlation of SARS-CoV-2 gene expression levels (UMIs) to the average UMI counts per spot.(a) Pearson correlation between the SARS-CoV-2 UMI counts per spot and the average human UMI counts per spot, p-value < 0.05.(b) Pearson correlation between the SARS-CoV-2 UMI counts per spot and the average SARS-CoV-2 UMI counts per spot, p-value < 0.05.

Figure S11 .
Figure S11.SARS-CoV-2 gene abundance dynamics.(a) The total number of singleton spots for each SARS-CoV-2 gene.(b) The total number of spots that 1, 2, 3, 4, 5, 6, 7, 8, or 9 different SARS-CoV-2 genes are detected in.(c) Number of spots and total UMI counts for each SARS-CoV-2 gene within the set of spots each particular SARS-CoV-2 gene is detected in.

Figure S12 .
Figure S12.SARS-CoV-2 gene colocalization metrics.Analytical p-values for the colocalization of SARS-CoV-2 gene pairs across the SARS-CoV-2+ spots from Chi-Square test for independence, Fisher's exact test, and Approximative (Monte Carlo) Pearson chi-squared test for independence (Permutation).The dotted vertical line indicates a significance threshold pvalue of 0.05.

Figure S16 .
Figure S16.Single cell deconvolution of ST clusters.Proportion of each single cell cell type across the ST clusters (top plots per cell type) and distribution of the proportion of each single cell cell type across the ST clusters (bottom plots per cell type).